This paper characterizes the set of equilibrium networks in the two-way flow model of network formation with small decay, and this for all increasing benefit functions of the players. We show that as long as the population is large enough, this set contains large- as well as small-diameter...

The novelty of our model is to combine models of collective action on networks with models of social learning. Agents are connected according to an undirected graph, the social network, and have the choice between two actions: either to adopt a new behavior or technology or stay with the default...

I study a one-way flow connections model in which players are heterogeneous with respect to values and the costs of establishing a link. I first show that values and costs asymmetries are crucial in determining the level of connectedness of a network. Interestingly, unconnected equilibria are...

This paper studies the impact of collaboration on research output. First, we build a micro-founded model for scientific knowledge production, where collaboration between researchers is represented by a bipartite network. The equilibrium of the game incorporates both the complementarity effect...

Policy makers spend large amounts of public resources on the foundation of science parks and other forms of geographically clustered business activities, in order to stimulate regional innovation. Underlying the relation between clusters and innovation is the assumption that co-located firms...

Agents involved in the formation of a social or economic network typically face uncertainty about the benefits of creating a link. However, the interplay of such uncertainty and risk attitudes has been neglected in the network formation literature. We propose a dynamic network formation model...

We study social learning in a social network setting where agents receive independent noisy signals about the truth. Agents naïvely update beliefs by repeatedly taking weighted averages of neighbors' opinions. The weights are fixed in the sense of representing average frequency and intensity of...

We study the impact of bots on social learning in a social network setting. Regular agents receive independent noisy signals about the true value of a variable and then communicate in a network. They na¨ıvely update beliefs by repeatedly taking weighted averages of neighbors' opinions. Bots...